This paper is in the following e-collection/theme issue:

Natural Language Processing (764) Clinical Informatics (1107) Ontologies, Classifications, and Coding (256) Machine Learning (1627) Secondary Use of Clinical Data for Research and Surveillance (399) Electronic Health Records (1124)

Published on in Vol 10, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37557, first published .
Automatic International Classification of Diseases Coding System: Deep Contextualized Language Model With Rule-Based Approaches

Automatic International Classification of Diseases Coding System: Deep Contextualized Language Model With Rule-Based Approaches

Automatic International Classification of Diseases Coding System: Deep Contextualized Language Model With Rule-Based Approaches

Authors of this article:

Pei-Fu Chen1, 2 Author Orcid Image ;   Kuan-Chih Chen1, 3 Author Orcid Image ;   Wei-Chih Liao1 Author Orcid Image ;   Feipei Lai1, 4, 5 Author Orcid Image ;   Tai-Liang He4 Author Orcid Image ;   Sheng-Che Lin4 Author Orcid Image ;   Wei-Jen Chen1 Author Orcid Image ;   Chi-Yu Yang6, 7 Author Orcid Image ;   Yu-Cheng Lin8, 9 Author Orcid Image ;   I-Chang Tsai10 Author Orcid Image ;   Chi-Hao Chiu11 Author Orcid Image ;   Shu-Chih Chang12 Author Orcid Image ;   Fang-Ming Hung13, 14 Author Orcid Image
Article Authors Cited by (10) Tweetations (3) Metrics

Journals

  1. Ariño H, Bae S, Chaturvedi J, Wang T, Roberts A. Identifying encephalopathy in patients admitted to an intensive care unit: Going beyond structured information using natural language processing. Frontiers in Digital Health 2023;5 View
  2. Chen P, He T, Lin S, Chu Y, Kuo C, Lai F, Wang S, Zhu W, Chen K, Kuo L, Hung F, Lin Y, Tsai I, Chiu C, Chang S, Yang C. Training a Deep Contextualized Language Model for International Classification of Diseases, 10th Revision Classification via Federated Learning: Model Development and Validation Study. JMIR Medical Informatics 2022;10(11):e41342 View
  3. Torres-Silva E, Rúa S, Giraldo-Forero A, Durango M, Flórez-Arango J, Orozco-Duque A. Classification of Severe Maternal Morbidity from Electronic Health Records Written in Spanish Using Natural Language Processing. Applied Sciences 2023;13(19):10725 View
  4. Zhang Y, Li X, Liu Y, Li A, Yang X, Tang X. A Multilabel Text Classifier of Cancer Literature at the Publication Level: Methods Study of Medical Text Classification. JMIR Medical Informatics 2023;11:e44892 View
  5. Nunes M, Bone J, Ferreira J, Elvas L. Health Care Language Models and Their Fine-Tuning for Information Extraction: Scoping Review. JMIR Medical Informatics 2024;12:e60164 View
  6. Zhuang Y, Zhang J, Li X, Liu C, Yu Y, Dong W, He K. Autonomous International Classification of Diseases Coding Using Pretrained Language Models and Advanced Prompt Learning Techniques: Evaluation of an Automated Analysis System Using Medical Text. JMIR Medical Informatics 2025;13:e63020 View
  7. Hatoum M, Charr J, Ghaddar A, Guyeux C, Laiymani D. NNBSVR: Neural Network-Based Semantic Vector Representations of ICD-10 codes. Applied Intelligence 2025;55(6) View

Books/Policy Documents

  1. Pedersen B, Islam M, Kristoffersen D, Bongo L, Garrett E, Reid A, Sommerseth H. Bridging the Gap Between AI and Reality. View
  2. Paraschiv E, Elena Cîrnu C, Victor Vevera A. Electronic Health Records - Issues and Challenges in Healthcare Systems [Working Title]. View